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Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance.

, , , , , and . CIKM, page 2487-2496. ACM, (2021)

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Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval., , , , , and . WSDM, page 1328-1336. ACM, (2022)Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models., , , , , , and . CIKM, page 2486-2496. ACM, (2022)Capability-aware Prompt Reformulation Learning for Text-to-Image Generation., , , , and . SIGIR, page 2145-2155. ACM, (2024)Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval (Extended Abstract)., , , , , and . IJCAI, page 6504-6508. ijcai.org, (2023)Leveraging Passage-level Cumulative Gain for Document Ranking., , , , , , and . WWW, page 2421-2431. ACM / IW3C2, (2020)Scaling Laws For Dense Retrieval., , , , , , and . SIGIR, page 1339-1349. ACM, (2024)An Analysis of BERT in Document Ranking., , , , and . SIGIR, page 1941-1944. ACM, (2020)Constructing Tree-based Index for Efficient and Effective Dense Retrieval., , , , , , and . SIGIR, page 131-140. ACM, (2023)Optimizing Dense Retrieval Model Training with Hard Negatives., , , , , and . SIGIR, page 1503-1512. ACM, (2021)Prompt Refinement with Image Pivot for Text-to-Image Generation., , , , , , , and . ACL (1), page 941-954. Association for Computational Linguistics, (2024)